Larridin

Larridin measures four dimensions of enterprise AI usage: adoption depth and fluency by team, workflow changes driven by AI, developer output and velocity from AI-augmented engineers, and granular spend across licenses, model calls, and tokens. Its platform connects to tools such as GitHub, Jira, and procurement systems to generate role-specific reporting for CIOs, CFOs, engineering leaders, and chief human resource officers.

Larridin does not publicly name any founders, executives, or investment principals on its website or any input source available to Altss. The firm’s ownership structure and management team are therefore unknown. This opacity is atypical for enterprise SaaS companies selling to C-suite buyers who typically evaluate leadership alongside the product.

Larridin positions itself as a dedicated measurement layer rather than a feature inside a broader platform. Its pitch to executives is that spend reports, adoption dashboards, and procurement data remain siloed in most organizations; Larridin’s specific value proposition is unifying those fragments into one source of truth for board-level AI reporting.

No. Larridin’s website cites a 47% average lift in team output and $2.4 million median AI spend optimization, but the company does not disclose the number of customers, the time period measured, or any third-party audit of these figures. The data should be read as vendor-supplied marketing claims.

Larridin’s website does not list a headquarters address, regional offices, or country-specific contact information. Its only public web presence is the domain larridin.com, which suggests an English-language North American orientation but provides no verifiable location data.